How to Learn Python for Machine Learning Online

If you’re just starting to learn a new skill, you can find dozens of tips and resources online; learning Python for machine learning is no different.Python is a general-purpose programming language for web development, data science, data analytics, and more. Machine learning is a subset of artificial intelligence concerned with automating tasks by leveraging data. If you’ve always wanted to learn Python for machine learning, there are plenty of options at your fingertips. From free tutorials to live classes, your options are outlined here so you can decide how to learn in a way that works best for you. 

What is Python for Machine Learning?

Python is an open-source, general-purpose programming language first developed in 1991. Because Python is open-source, it is free and publicly available for anyone to use. Python can be used to build websites, develop software, conduct data analysis, and automate tasks using artificial intelligence (AI) and machine learning. 

Machine learning enables computer systems to automatically learn and adapt without manual input. The system does this by using statistical models and algorithms to detect patterns in data. Python’s libraries and frameworks, along with the coding language’s platform independence, popularity and community, concise and readable code, flexibility, and consistency, make it a perfect fit for machine learning. 

Read more about what Python is and why you should learn it for machine learning.

What Can You Do with Python for Machine Learning?

Python is a general-purpose programming language that you can use to create data visualizations, write programs for machine learning, analyze data, make file directories, build apps, and more. Because of its many applications in using and managing data, Data Scientists must have a thorough knowledge of Python programming and its uses. 

Python for machine learning is used to personalize and improve user experiences. Machine learning can automate customer support, detect fraudulent transactions, recommend products, refine search engine results, automate translation, recommend music, and predict the effectiveness of drug treatments. There are countless uses for machine learning and demand is only increasing, making now an opportune time to learn Python for machine learning.

Live Online Python for Machine Learning Training

When researching Python for machine learning, you may wonder if live online classes are the best way to learn. Live online classes come with many benefits, but there are also a few drawbacks to consider. Benefits include collaborating with classmates, asking your instructor questions in real-time, and getting instant step-by-step guidance on hands-on assignments. Other positives include the ability to learn remotely so you never have to commute and you can choose from classes offered worldwide. Drawbacks to the live online training format are that classes meet at a designated time, which is difficult if you have a packed schedule, and that unlike in-person classes, live online classes do not offer the chance to network on the local level. You will also need to ensure that you have all the necessary equipment and software to complete your live online class, which can be an extra expense. For most students, the positives far outweigh the negatives when taking a live online class. You can also get the most out of your live online class by finding courses with additional benefits like flexible payment plans, free retakes, 1-on-1 mentoring, and job search assistance.

You can use the Classes Near Me tool to explore and compare live online Python for machine classes.

On-Demand Python for Machine Learning Classes

On-demand courses are also known as self-paced courses because they have few, if any, hard deadlines, relying on you to advance at your own pace. This flexibility works well for those with an unconventional or packed schedule. On-demand courses consist primarily of video content, which allows you to pause and rewatch lessons whenever you wish. You can explore free video content covering introductory topics such as Python basics or advanced topics like Python for machine learning. You can also find paid video courses on platforms like Coursera, Udemy, and LinkedIn Learning for around $30 to $60 per month, making this educational option highly affordable. 

The main drawback to keep in mind when exploring on-demand training options is that self-paced classes often lack instructor access. If you have a question or have technical issues, you may have to wait several hours or days to receive an email reply. And the more complex a topic is, the more beneficial it is to have real-time feedback from an instructor. Still, on-demand classes can benefit in learning introductory skills and gaining a high-level overview of a topic before committing to a more expensive training method.

Learn more about on-demand Python for machine learning courses.

Free Intro Courses & Tutorials

Before committing to a paid training method, you may want to explore free resources that provide an overview of Python for machine learning. Free resources can help you build foundational skills, understand the advantages and challenges of learning Python for machine learning, meet the necessary prerequisites, and help you decide how you want to learn this skill. 

Before learning Python for machine learning, you must have a firm foundation in Python programming and understand the NumPy and Pandas libraries. In Noble Desktop’s free video seminar Intro to Python Fundamentals, you will learn about the Python programming language and its many uses in data science and data analytics.

You can also find free introductory Python courses from Google, Microsoft, and on learning platforms like Udemy and Coursera.

Read about more free Python for machine learning videos and online tutorials.

Comparing Online Methods with In-Person Learning 

When comparing available training methods for machine learning with Python, you should consider the benefits and drawbacks of each format. Also consider your learning style, schedule, career goals, and budget. The three training methods are on-demand, in-person, and live online classes. This section will compare each training format to help you choose the best fit for your needs. 

On-demand/self-paced classes primarily consist of pre-recorded video content. The self-paced nature of these courses and their affordability make them a popular learning method. You can explore free on-demand classes on Python and machine learning or complete paid courses through subscriptions to platforms like Udemy, LinkedIn Learning, and Coursera. These paid subscriptions cost around $30 to $60 per month. Some courses take multiple months to complete, making this a recurring rather than a one-time payment. Videos are easy to view on desktop and mobile devices. They provide visual and audible content, which benefits visual and auditory learners. You can also pause and replay the video as often as you need, which helps you retain the information long-term. This learning method's main drawback is having no instructor access or very limited access. When you are stuck waiting hours or days for an emailed response to your question, it grinds all progress to a halt. For this reason, many people use on-demand classes to introduce a topic, then follow up with instructor-led courses. 

Instructor-led courses include in-person classes and live online classes. Both formats are led by instructors in real-time, allow you to interact and collaborate with classmates, and provide instant feedback when you have questions or are working through a hands-on activity. In-person classes have the advantage of letting you network locally and providing all necessary equipment, such as a computer loaded with the tools you need. Live online classes can let you learn from anywhere, with no need to commute. With live online classes, you can enroll in courses based in distant places, which gives you a much wider selection of available courses. Whether you meet in person or live online, you will want to find a class time that works for your schedule and a curriculum that covers the skills needed to reach your career goals. Also, consider whether part-time or full-time enrollment fits your needs. Part-time classes tend to meet in the evenings and on weekends, making it more convenient for those with weekday jobs. If you can commit to a full-time class schedule, you can typically complete a program in half the time, for example, reducing a six-month program to three months.

Tips to Succeed when Learning Python for Machine Learning Online

You can use online classes in more ways than you might realize. When you think of online classes, the first thing to come to mind might be on-demand courses like those on LinkedIn Learning, Udemy, and Coursera. You may also think of video classes found on YouTube. However, online classes also include live virtual classes that connect you to classmates and an instructor in real-time. How you use these different online class types will depend on your learning style, goals, and the learning methods you choose, but there are tips anyone can use to make the most of online class options. This section will detail tips to help you learn Python for machine learning online.

Determine Your Goals

Before you decide what online classes and learning methods to explore, you should determine your goals. What do you hope to gain with Python for machine learning? Are you adding this skill to your resume to advance your current career? Are you looking to start a new career in a field like data science? Are you focusing on just learning Python for machine learning, or is this one skill among many you intend to learn? Knowing your goals will allow you to determine the exact skills and resources you need to achieve those goals. You can then explore online classes with broad curriculums, specific focuses, self-paced schedules, set schedules, hands-on activities, mentoring, live instructors, and more to determine the right fit.

Know The Prerequisites

Before learning Python for machine learning, you must first master the Python programming fundamentals. 

Python is considered a beginner-friendly programming language, but knowing another language makes the process easier. If you want to start with a programming language even more basic than Python, you can begin with HTML and CSS. Noble Desktop’s beginner-friendly Intro to HTML & CSS class is a live online course that teaches you how to use HTML and CSS for formatting paragraphs, headings, and lists, creating links, and adding images. You can follow this class up with the Advanced HTML & CSS class. To learn the Python programming fundamentals and Python’s uses in data science, you can enroll in Noble Desktop’s Python for Data Science Bootcamp. 

If you want to learn Python fundamentals and Python for machine learning in a single course, consider Noble’s Python for Data Science & Machine Learning Bootcamp.

Those wishing to learn Python for machine learning to pursue a career in data science may wish to learn more about Noble Desktop’s Data Science Certificate program.

Know Your Learning Style

Are you a kinesthetic learner that best learns skills by doing hands-on activities? Are you a visual learner that retains information by viewing it, or an auditory learner that learns best by hearing information? Most people benefit from a combined teaching method that uses tactile, visual, and audible elements. Knowing your dominant learning style will help you decide what training method works best for you. On-demand videos provide visual and audible elements that can be paused and repeated. Some on-demand courses may also include hands-on activities you complete by following along with the video or following written instructions. Live online classes combine lectures, video interaction, and hands-on projects with real-time instruction. The main advantage of a live online class over an on-demand class is the ability to ask an instructor your questions as they arise, without pausing your lesson waiting for an emailed response. 

Determine Your Budget

How much are you willing or able to spend on a class? What is the cost of an on-demand class compared to a live online class? When considering your budget, you should compare the upfront costs of online classes, but also consider which option provides the best long-term value. For example, on-demand classes cost far less than instructor-led courses, however, if a live online class includes flexible payment plans which reduce the upfront costs and includes benefits that are more likely to advance your career, it may be the better long-term investment. Look for live online classes that include mentorship, professional portfolio and resume review, and other job search assistance benefits that can help you achieve your career goals.

Research Your Options

One of the best parts of learning online is that you are not limited to courses offered in your local area. You can take classes taught around the world, from wherever you choose. You can choose from on-demand classes and live online classes. Noble Desktop’s Classes Near Me tool can show you live online Python for machine learning classes to compare course benefits, schedules, and offerings.

Set a Schedule

The key to developing a habit is to perform the task repeatedly and consistently. If you are taking an on-demand/self-paced class, you will need the self-discipline to learn and practice regularly. The flexibility that asynchronous classes offer makes it tempting to pick up and put down the class without a set schedule, but scheduling a consistent time to learn and practice means you are more likely to stay on track and complete the course. Live online classes come with some regularity of schedule built-in. Classes meet at specific times, often in the evenings and on weekends, so students with daytime obligations can attend. You can find live online classes that work for your schedule. Even with consistent class times built-in, you may wish to further develop your skills by practicing outside of class hours. In that case, setting a consistent time for practice will help you make it part of your daily or weekly routine.

Get Hands-On Experience

If you take on-demand classes, you can get hands-on experience by following video tutorials or written instructions. Some on-demand classes include downloadable tools, templates, and exercises so that you can put the skills you learn into practice. Live online classes include hands-on activities that you advance through step by step with your instructor’s guidance. Live online classes may include interactive projects you complete by collaborating with classmates. Many hands-on projects will also be based on real-world scenarios so that you can get practicle experience. You can include such projects in a professional portfolio to show employers your capabilities. 

Ask Questions

Be sure to ask your mentor or instructors questions so you can better understand your topic, learn best practices, and make the most of the projects you complete. If you wish to take on-demand classes, look for those that include some instructor outreach through email or office hours. For live online classes, you can ask your questions as they come up. 

Key Insights

• You can take online classes that cover Python for machine learning. 
• Online class types include on-demand courses and live online classes.
• On-demand classes consist of pre-uploaded material that you work through at your own pace.
• Live online classes connect you to classmates and an instructor in real-time at scheduled times. 
• Before learning Python for machine learning, you must master Python programming fundamentals.
• You can start learning online with free resources such as free video classes and introductory material.
• Tips to succeed when learning online include outlining your goals, knowing your learning style, determining your budget, researching class options, setting a schedule, gaining hands-on experience, and asking questions of your instructor. 

Learn Python for Machine Learning with Hands-on Training at Noble Desktop

Noble Desktop offers instructor-led courses that provide hands-on experience using Python for machine learning. You can take a specialized course such as the Python for Machine Learning course or learn this skill through the Data Science Certificate program. 

The Python for Machine Learning course requires students to have a strong foundation in Python programming and its data science libraries NumPy and Pandas prior to enrollment. If you do not have previous experience with Python programming, you can satisfy this prerequisite by first taking Noble’s Python for Data Science Bootcamp.

If you want to learn Python for machine learning as part of a broader curriculum, especially if you want to launch a new career in data science, the Data Science Certificate program covers essential skills in a single program. This program includes small classes, 1-on-1 mentoring, setup assistance, a free retake, flexible payment options, hands-on experience, and job search assistance.

Explore live online Python for machine learning classes that connect you to expert instructors for real-time feedback and guidance.